Relationship of subjective and objective sleep measures with physical performance in advanced-stage lung cancer patients

Advanced lung cancer patients suffer from deteriorated physical function, which negatively impacts physical and psychological health. As little is known about sleep and physical function in this population, this study aimed to examine the association between subjective and objective sleep parameters and physical function among them. 164 advanced lung cancer patients were included. Objective sleep was measured by actigraphy (measured on non-dominant wrist for 72 h), and subjective sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). Performance-based physical function was measured by Timed Up and Go Test (TUGT), 6-Minute Walk Test (6MWT), Sit-to-Stand Test, and One-leg Standing Test. Univariable and multivariable regression analyses were employed to examine the association between sleep and physical function. Total sleep time (TST) was significantly associated with the 6MWT (β = 0.259; 95% CI 0.120, 0.398; P < 0.001), TUGT (β = − 0.012; 95% CI = − 0.017, − 0.008; P < 0.001) and Sit-to-Stand Test (β = 0.027; 95% CI = 0.018, 0.035; P < 0.001) after adjustment for multiple covariates. PSQI global score was only significantly associated with TUGT (β = 0.140; 95% CI = 0.000, 0.280; P = 0.050) after adjustment for multiple covariates. Shorter sleep duration significantly predicted poorer physical performance in advanced lung cancer patients, and more attention is required for those with less than 4.3 h of sleep on average. Trial registration: ClinicalTrials.gov, NCT03482323. Registered 29 March 2018, https://clinicaltrials.gov/ct2/show/NCT03482323; ClinicalTrials.gov, NCT04119778. Registered 8 October 2019, https://clinicaltrials.gov/ct2/show/NCT04119778.

Factors associated with physical function in advanced cancer patients include fatigue and performance status 7 . Sleep is another potential factor related to physical function that deserves further investigation in cancer populations. Several studies conducted among athletes demonstrated that sleep deprivation negatively impairs their physical performance and increases their reaction time and perceived exertion during exercise 8,9 . There is also emerging evidence in community-dwelling elderly individuals that self-reported sleep disturbances, together with objectively measured poor sleep, are associated with slower walking speed, weaker muscle strength, and functional performance impairment [10][11][12] . For cancer populations, two studies showed that patients with insomnia had more physical impairment 13,14 . However, both studies adopted self-report sleep questions that were subject to reporting bias 13,14 . Additionally, only one study used a validated physical performance test (Short Physical Performance Battery) 14 , while another used a self-report questionnaire 13 .
There has been no research examining the association between sleep and physical functions in cancer populations utilizing both subjective and objective sleep measures and validated physical performance tests. Among different cancer types, lung cancer was found to be associated with poor physical function and functional decline over time in patients 15 . Additionally, patients with lung cancer had either the highest or second-highest level of sleep problems compared to other cancer populations 15,16 . Therefore, the present study aimed to examine the association between subjective and objective measures of sleep parameters and performance-based measures of physical function in advanced lung cancer patients. It is hypothesized that both subjective and objective sleep parameters predict physical performance in this population. Our findings shed light on whether sleep predicts physical performance in an advanced lung cancer population. Such information will guide sleep assessment in cancer patients for predicting physical function and related outcomes, including quality of life and survival.

Methods
Participants. This study reports a subset of baseline data from a randomized controlled trial examining the effect of exercise in patients with advanced-stage lung cancer. The trial was registered with ClinicalTrials.gov (identifier: NCT03482323 registered on 29/3/2018) and (identifier: NCT04119778 registered on 8/10/2019). Patients were eligible if they were (1) diagnosed with stage IIIB or IV non-small cell lung cancer; (2) of 0-2 Eastern Cooperative Oncology Group Performance Status; (3) not diagnosed with other cancer a year before; (4) not exercising regularly (defined as < 150 min of moderate-intensity exercise per week) in daily living; and (5) not participated in current research studies or other aerobic exercise or mind-body exercises. Patients were excluded from the study if they were suffering from a clinically diagnosed neurological, or psychiatric disorder and had not completed the questionnaires or physical functioning tests.
Procedures. Patients were approached by research personnel and recruited from outpatient clinics at three hospitals in Hong Kong from May 2018 to Jan 2020. Written informed consent was obtained from all patients before questionnaires and functioning tests commenced. At study entry, patients completed the questionnaires and physical functioning tests conducted by research personnel following standard protocols [17][18][19][20] 21 . The PSQI is a self-completed, validated questionnaire that assesses sleep quantity and quality during the past month. It consists of 19 questions that encompass seven dimensions: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, sleep medication usage, and daytime dysfunction 21 , and thus provides a relatively more detailed assessment of sleep quality than other sleep measures. Each dimension score ranges from 0 to 3, rendering a total score of 0 to 21 in which score level negatively is correlated with sleep quality. A total score > 5 denotes poor sleep 21 . The PSQI has been validated in the Chinese population 22 . In addition, the PSQI has been found to be a reliable and valid measure of sleep in cancer patients 23 , and is the most commonly used tool to assess sleep quality in cancer patients in two recently published reviews 24,25 .
Objective sleep parameters. Sleep was also assessed objectively by using wrist actigraphy (Actigraph; Ambulatory Monitoring Inc., New York). An actigraph was worn on the non-dominant wrist for 72 h. Participants were asked to complete a sleep diary for the duration of time they wore the actigraph which was used to revise the actigraphy data.
Sleep parameters measured by actigraphy included the following: (1) total sleep time (TST), defined as the hours per night spent sleeping while in bed; (2) sleep efficiency, calculated as TST divided by the time between bedtime and rise-time multiplied by 100; (3) wake after sleep onset, measured as the sum of all wake epochs during the sleep period (reflecting the number of minutes that exceeded the sensitivity threshold and were scored as awake); and (4) the movement and fragmentation index (MFI), the number of interruptions of sleep by physical movement, calculated as the number of groups of consecutive mobile 20-s epochs divided by the total number of immobile epochs multiplied by 100. The MFI captures all movements regardless of the intensity of the movement 26 . Actigraphy data for each patient were averaged over a 24-period to reduce night-to-night variability.

Physical functioning tests. Timed up and go (TUGT). The Timed Up and Go Test is a test of balance
that is commonly used to examine an individual's functional mobility 17 . It measures the time an individual needs to stand up from a standard armchair, turn, walk back, and sit down. The time taken to complete the test is strongly correlated with the level of functional mobility. This is a reliable and valid test for quantifying functional www.nature.com/scientificreports/ mobility, which is a term used to reflect the balance and gait manoeuvres used in everyday life (e.g., getting in and out of the chair, walking, and turning) 17 .
Sit-to-stand test. The sit-to-stand test is used to measure an individual's lower limb strength, and it measures the number of repetitions an individual has completed in a given period from a chair 18 . An individual is instructed to have their hands folded in front of the chest with their feet flat on the floor. The test has been reported to be associated with standing, leaning balance 27 , and mobility 27 .
6-minute walk test. The 6-min walk test (6MWT) measures the distance an individual can walk at a constant, uninterrupted, and unhurried pace in 6 min 20 . It is a simple and inexpensive method for assessing exercise capacity at a submaximal level. All 6MWTs were conducted using a lap 20-25 m in length on flat, hard ground, according to the American Thoracic Society guidelines 28 . Walk tests were timed with a stopwatch. The number of full laps completed was counted, and the distance covered in the last lap was determined; hence, the total distance in metres was calculated for each walk.
One-leg standing test. One-leg standing test measures the time one can stand on one lower limb without support 19 . This test is a clinical tool that assesses postural steadiness in a static position by quantitative measurement 29 . An individual is asked to stand initially in a relaxed stance with their weight evenly distributed between both legs. Without using any assistive device, he/she is instructed to stand on the leg they select while keeping their arms by their sides. Their eyes remain open during the test.
Covariates. Predisposing factors that were known to affect both sleep and physical function in cancer patients encompassing background characteristics, psychological distress, fatigue, and daily physical activity level were measured 7,30-33 .
Background characteristics. Sociodemographic variables, cancer-related information, and lifestyle factors were collected via a self-designed questionnaire. Sociodemographic variables included age, gender, marital status, and education level. Cancer-related information comprised current treatment modalities (chemotherapy or nonchemotherapy), time since diagnosis, and lifestyle factors consisting of smoking (smoker or nonsmoker) and drinking (drinker or nondrinker) habits. Body mass index (BMI) was calculated as weight in kilograms divided by height in metres squared. The Karnofsky Performance Status (KPS) score, which measures the level of patient activity and patient independence, was assessed by nurses 34 .
Psychological distress. Psychological distress (i.e., anxiety and depression symptoms) was measured using the Chinese version of the Hospital Anxiety and Depression Score (HADS), with a score of 8 or more on either subscale representing clinical cases of anxiety or depression 35 .
Fatigue. Fatigue was assessed using the Chinese version of the Brief Fatigue Inventory (BFI), comprising 9 items with each scored on a 0-10 numeric scale 36 . A higher score indicates a higher level of fatigue.
Daily physical activity level. Daily physical activity level (i.e., step count) was measured via actigraphy.
Charlson comorbidity index (CCI). The Charlson Comorbidity Index was developed to estimate the 1-year mortality risk and disease burden 37 . The CCI takes into account 19 comorbid conditions with each comorbidity weighted 1, 2, 3, or 6 for its relative risk of 1-year mortality 37 . The CCI has demonstrated excellent predictive validity for numerous clinical outcomes and a number of malignancies 38 .

Statistical analysis.
Descriptive statistics were used to describe the sociodemographic, clinical, and treatment characteristics of the patient population. Characteristics were summarized as the mean ± standard deviation (SD) for continuous variables and counts and percentages for categorical variables. Regression analysis was employed to estimate the association between subjective (PSQI global score and its seven components) and objective sleep measures (actigraphy, i.e. total sleep time, sleep efficiency, and wake after sleep onset) and physical functioning tests (6-Minute Walk Test, One-leg Stand Test, Timed Up and Go Test, and Sit-to-Stand Test). Univariable regression analysis was first performed to examine the association of a single sleep measure with each physical functioning test. Subsequently, multivariable regression analysis was performed with covariates added to the linear model. The covariates added included age, gender, BMI, education, time since diagnosis, current treatment, marital status, KPS score, step count per day, smoking, drinking, fatigue, anxiety, depression, and CCI. For both models, data were checked for a linear relationship, absence of multicollinearity, homoscedasticity, and a normal distribution of residuals.
A receiver operating characteristic (ROC) curve analysis was conducted to determine a cut-off value for each sleep parameter that best identified individuals with poor physical performance. Specifically, it was taken as the one that maximized the Youden index, that is, sensitivity + specificity−1. The accuracy and utility of the cut-off were assessed by the sensitivity, specificity, and positive and negative predictive values.

Discussion
The current study showed that shorter sleep duration as measured by actigraphy was independently associated with lower physical function as measured by the 6MWT, Sit-to-Stand Test, and Timed Up and Go Test. These associations remained even after adjustment for multiple potential confounding factors.
Our study is the first to report that shorter sleep duration as measured by actigraphy was associated with poorer physical function in cancer patients. This finding is in line with previous studies conducted among healthy and ill populations which found that sleep deprivation gives rise to more physical impairment 11,13,39 . The underlying mechanism between sleep duration and physical function remains unknown. One plausible mechanism is that sleep deprivation leads to immune system dysregulation, including a significant reduction in natural killer cell activity and an increase in pro-inflammatory cytokines 9,40 . A dysregulated immune system might be associated www.nature.com/scientificreports/ with a destructive metabolic profile and increased inflammatory risk 9 , which could subsequently contribute to sarcopenia, frailty, and functional decline 41 . Future research is warranted to investigate the exact underlying reasons for the physiology that link sleep duration and physical function in cancer patients. Of note, two studies conducted among a general elderly population reported that self-reported longer sleep duration is associated with greater physical function decline 42,43 . The discrepancy of the results may be attributed to the tendency of the elderly to overestimate the subjective total sleep time compared with objectively measured sleep duration. Future studies should adopt both subjective and objective measures of sleep to ensure the reliability of the sleep quality reported. Our study revealed that subjective quality of sleep did not predict performance on the 6MWT, Sit-to-Stand Test, or One-leg Standing Test, which is in line with the results of a previous study in older adults with cancer demonstrating the insignificant association between self-reported sleep disturbance and impairment on the Short Physical Performance Battery 14 .
Interestingly, we found that the subjective quality of sleep significantly predicted TUGT. Additionally, among the physical function tests, the TUGT appears to be comparatively sensitive to reflect associations with both subjective and objective sleep measures compared to the 6MWT, Sit-to-Stand Test, and One-leg Standing test. The TUGT test encompasses numerous activity themes, namely, sit-to-stand and stand-to-sit transitions, walking, and turning, and it is often used to distinguish subjects at risk of falling 44 . Meanwhile, the other three functioning tests merely involve one activity theme: the Sit-to-Stand Test incorporates sit-to-stand and stand-to-sit transitions; the 6MWT incorporates walking and turning, and the One-leg Standing Test incorporates knee flexion 44 . It is possible that TUGT covers a wider range of physical functions and thus is more reflective of the influences exerted by poor sleep. Poor sleep is associated with greater drowsiness, poorer concentration 45 , and cognitive deficits, including abated attention and lengthened reaction time 45,46 , thereby affecting physical performance. Further studies should be conducted to study the mechanisms underlying the association between TUGT and sleep outcomes.
Concerning the performance in physical tests, our sample performed poorer in the majority of the physical functioning tests, specifically in the TUGT, Sit-to-Stand Test, and 6MWT when compared to prior studies conducted among various cancer populations. Regarding TUGT, prostate cancer patients with no distant metastasis required less time (5.2 to 7.2 s) 47 than our sample (8.77 s). For the Sit-to-Stand Test, studies in mixed cancer types reported a range of 9 to 19 times 48-50 , while our sample completed merely 8 repetitions on average in 30 s. Regarding the 6MWT, patients with mixed cancer types walked 427 to 594 m 48,50,51 , while our sample walked 403 m in 6 min on average. Our findings suggest that advanced lung cancer patients are likely to be frailer and more vulnerable in regard to physical performance compared with other cancer populations, such as prostate, breast, and head and neck cancer. However, a comparison should be interpreted with caution considering the varied stages of cancer and study settings.
This study has several strengths. This is the first study to examine the relationship between sleep and physical performance among advanced lung cancer patients. Additionally, both subjective and objective measures of www.nature.com/scientificreports/ www.nature.com/scientificreports/ sleep were employed to assess sleep parameters, and the reliability of the results was ensured. Another strength is that the physical functioning tests performed were objective and performance-based. This study also has some limitations. First, this study was a cross-sectional study, and whether sleep duration precedes functional decline could not be determined. Second, there may be confounding factors, such as complications, chronic diseases, and pain medication use, namely opioid or psychotropics, which were not measured in our study. Furthermore, the sample size was limited and might narrow the generalizability. Future studies should include a larger sample size. Last, the optimal cut-off value of total sleep time must be validated by an independent and larger sample in the future (Fig. 1).

Conclusions
In conclusion, our study showed that shorter sleep duration significantly predicted poorer physical performance in advanced lung cancer patients. Sleep deprivation appeared to be a significant issue that requires more attention from researchers and healthcare professionals. Intervention to ameliorate sleep deprivation is encouraged to be implemented among lung cancer patients, whilst healthcare professionals should pay more attention to the quantity of sleep in lung cancer patients, specifically for those with less than 4.3 h of sleep on average, when assessing and evaluating their condition.

Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. www.nature.com/scientificreports/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.